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ReAct

Appears in 7 awesome lists

The foundational paper defining the Thought/Action/Observation loop structure that underlies virtually every agent harness. Required reading for understanding why the loop is structured the way it is and where each harness component maps onto the reasoning-acting cycle.

Open arxiv.org

Found in these lists

Awesome Ai Agents 2026

Section: Key Papers · Foundation for modern agents (reasoning + acting)

ActiveScore 74

Awesome AI Papers

Section: NLP

SlowScore 51

Awesome Artificial Intelligence

Section: Foundational papers · Combined reasoning traces with actions for tool-using language-model agents.

FreshScore 86

Awesome Forward Deployment Engineering (FDE)

Section: The Fundamental Whitepapers · The logic behind how Agentic systems (like Google ADK) actually work.

FreshScore 83

Awesome GPT Prompt Engineering

Section: Papers

SlowScore 65

Awesome Harness Engineering

Section: Agent Loop · The foundational paper defining the Thought/Action/Observation loop structure that underlies virtually every agent harness. Required reading for understanding why the loop is structured the way it is and where each harness component maps onto the reasoning-acting cycle.

FreshScore 88

Awesome Prompts

Section: Foundations · Reasoning + Acting interleaved — foundation of agent prompt design

FreshScore 90

ChatGPT

Announcement of ChatGPT, a conversational model trained to answer follow-up questions, admit mistakes, challenge incorrect premises, and reject inappropriate requests. OpenAI blog, November 30, 2022.

In 8 listsDetails

Attention Is All You Need

(AIAYN) - Introducing multi-head self-attention neural networks with positional encoding to do sentence-level NLP without any RNN nor CNN - this paper is a must-read (also see this explanation and this visualization of the paper).

In 6 listsDetails

Training language models to follow instructions with human feedback

This paper presents an RLHF approach to using supervised learning to fine-tuning. It is also known as a paper that illustrates the kernel of ChatGPT's thinking. Presumably, ChatGPT is an extended version of InstructGPT that enables fine-tuning on larger datasets.

In 6 listsDetails

Chain-of-Thought Prompting

foundational result; intermediate reasoning steps improve performance.

In 5 listsDetails

HuggingGPT

Solving AI Tasks with ChatGPT and its Friends in HuggingFace

In 5 listsDetails

Generative Agents: Interactive Simulacra of Human Behavior

a paper that presents computational software agents that simulate believable human behavior

In 5 listsDetails

Tree of Thoughts

search over reasoning trees.

In 4 listsDetails

Language Models are Few-Shot Learners

by Tom B. Brown (OpenAI) et al. - "We train GPT-3, an autoregressive language model with 175 billion parameters :scream:, 10x more than any previous non-sparse language model, and test its performance in the few-shot setting."

In 4 lists